内容来源：https://www.wired.com/story/model-behavior-loyalty-is-dead-in-silicon-valley/

内容总结：

硅谷正经历一场由人工智能驱动的“人才大迁徙”。去年以来，Meta、谷歌、英伟达等科技巨头已斥资数百亿美元，通过收购式招聘将多家AI初创公司的核心团队及技术收入囊中。与此同时，顶尖AI实验室之间也上演着激烈的人才争夺战，OpenAI、Anthropic等机构的研究人员频繁流动，形成“人才旋转门”现象。

风险投资机构GV的投资者戴夫·穆尼奇耶洛将这一趋势称为科技初创公司的“大解绑”。过去，创始团队往往坚守至公司上市或关停；如今，在生成式AI迅猛发展、资本充裕的背景下，投资者已默认“投资一家可能被拆分的初创公司”成为新常态。

高额薪酬无疑是吸引人才流动的重要因素。据报道，Meta曾为顶级AI研究员开出数千万甚至上亿美元薪酬包。但普林斯顿大学计算机科学家萨亚什·卡普尔指出，更深层的原因在于行业文化变迁：员工对长期效力单一机构的忠诚度下降，更注重个人影响力与机遇。许多初创公司创始人亦更加务实，倾向于借助大公司的资源扩大技术影响。

为应对人才流动带来的不确定性，投资者开始更严格评估创始团队的凝聚力，并在投资协议中增设知识产权保护条款。然而，这种高速流动也折射出AI行业的加速特性——《连线》资深记者史蒂文·利维指出：“在AI初创公司工作一年，相当于过去科技行业创业公司五年的经历。”产品迭代周期极短，使从业者技能快速成熟，进而追求更大挑战。

与上世纪八九十年代科技人才稀缺、流动缓慢的局面相比，当前AI人才面临前所未有的选择空间。但行业光环渐褪，理想主义让位于实用主义。在技术狂奔的节奏中，人才争夺战已推高人力成本至历史高位。这场以天价薪酬和频繁跳槽为标志的行业剧变，最终将把AI竞争引向何方，仍是悬而未决的命题。

中文翻译：

自去年年中以来，硅谷至少发生了三起重大的人工智能"收购式招聘"。Meta向Scale AI投资逾140亿美元，并招揽了其首席执行官亚历山德·王；谷歌斥资24亿美元获得Windsurf技术授权，并将其联合创始人和研究团队并入DeepMind；英伟达则豪掷200亿美元押注Groq的推理技术，并聘用了其首席执行官及其他员工。

与此同时，前沿人工智能实验室正在上演一场高风险且似乎永无止境的人才争夺战。最新一轮洗牌始于三周前——OpenAI宣布重新聘用数名两年前离职加入米拉·穆拉蒂初创公司Thinking Machines的研究人员。与此同时，由OpenAI前员工创立的Anthropic公司，正从ChatGPT制造商那里挖走人才。而OpenAI则刚刚聘请了一位Anthropic前安全研究员担任其"防范准备部门负责人"。

正如GV风投机构投资人戴夫·穆尼基耶洛所言，硅谷正在发生的招聘动荡体现了科技初创企业的"大解体"。在早期时代，科技创始人及其首批员工通常会坚守岗位，直到公司倒闭或出现重大流动性事件。但在当今生成式人工智能初创公司迅猛发展、资金充裕、且研究人才实力备受重视的市场环境下，穆尼基耶洛坦言："如今投资初创企业时，你已预见到它可能分崩离析。"

最炙手可热的人工智能初创公司的早期创始人和研究人员因各种原因在不同公司间流动。对许多人而言，金钱无疑是重要驱动力。据报道，去年Meta为顶级人工智能研究人员提供的薪酬方案高达数千万甚至数亿美元，不仅提供尖端计算资源，更承诺创造"世代财富"。

但普林斯顿大学计算机科学研究员、Mozilla高级研究员萨亚什·卡普尔指出，这并非全然为了致富。近年来震撼科技行业的广泛文化变迁，使一些从业者担忧长期效力于单一公司或机构。雇主过去可以放心假设员工至少会工作满四年——这是股权激励通常的归属期。在21世纪初至2010年代理想主义盛行的时期，许多早期联合创始人和员工也真诚信奉公司的既定使命，渴望助力实现目标。

卡普尔表示，如今"人们更清楚所在机构的局限性，创始人也更加务实"。他以Windsurf创始人为例指出，他们可能评估认为在谷歌这样资源雄厚的平台能产生更大影响力。卡普尔补充说，学术界也正发生类似转变——过去五年间，他目睹越来越多博士研究员中断计算机科学博士项目投身工业界。在人工智能创新飞速发展的当下，固守一处意味着更高的机会成本。

警惕成为人工智能人才争夺战附带损害的投资人正在采取自我保护措施。Striker Venture Partners创始人马克斯·加佐尔表示，其团队"比以往更注重考察创始团队的化学反应与凝聚力"。他透露，交易合同中日益普遍地包含"保护性条款，要求重要知识产权授权或类似场景必须获得董事会批准"。

加佐尔指出，近期部分重大收购式招聘涉及当前生成式人工智能热潮前成立的初创企业。例如Scale AI成立于2016年，当时王与Meta达成的这类交易对许多人而言难以想象。但如今加佐尔解释，这些潜在结果可能在早期条款清单中被纳入考量并"进行建设性管理"。

当我向报道硅谷数十年的同事史蒂文·利维询问对此文化变迁的看法时，他指出过去几年在人工智能初创公司工作为许多创始人和顶尖研究者提供了加速成长体验。

"在人工智能初创公司工作一年，相当于在科技行业不同时代的初创公司工作五年。"利维说。如今团队能在较短时间内推出数百万人使用的新产品，这让从业者感觉技能已得到充分磨练，可以迎接更大挑战。

这代科技从业者比前辈拥有更广阔的选择空间。在米拉·穆拉蒂的Thinking Machines实验室诞生数十年前，曾有一家同名公司致力于并行计算与人工智能研究。其早期员工卢·塔克回忆，1986年入职时公司约50人，到1996年破产被太阳微系统公司收购时已超500人。"当时几乎没人离职，"塔克解释道，那时也没有招聘网站，人们全靠"毛遂自荐"。

即便在21世纪科技成为主流后，许多创始人和早期员工仍对公司保持忠诚。拒绝臃肿科技巨头的收购要约、坚守初创事业曾是值得夸耀的资本。谷歌、脸书、爱彼迎、Stripe、Pinterest、Slack、Notion等公司的创始人及元老们坚守多年，最终收获了忠诚的回报。

但此后科技行业的光环已大幅褪色。创始人及其最忠诚的追随者正用理想主义交换实用主义。人工智能发展日行千里，开发者们亦奋力追赶。在下一个机遇降临前，他们鲜有余裕徘徊驻足或缓慢积累声誉。眼下，这代人工智能人才尚可自定身价。但问题在于：代价究竟几何？

本文系《模范行为》时事通讯系列报道之一，帕雷什·戴夫参与补充报道。过往通讯内容可通过此处查阅。

英文来源：

Since the middle of last year, there have been at least three major AI “acqui-hires” in Silicon Valley. Meta invested more than $14 billion in Scale AI and brought on its CEO, Alexandr Wang; Google spent a cool $2.4 billion to license Windsurf’s technology and fold its cofounders and research teams into DeepMind; and Nvidia wagered $20 billion on Groq’s inference technology and hired its CEO and other staffers.
The frontier AI labs, meanwhile, have been playing a high stakes and seemingly never-ending game of talent musical chairs. The latest reshuffle began three weeks ago, when OpenAI announced it was rehiring several researchers who had departed less than two years earlier to join Mira Murati’s startup, Thinking Machines. At the same time, Anthropic, which was itself founded by former OpenAI staffers, has been poaching talent from the ChatGPT maker. OpenAI, in turn, just hired a former Anthropic safety researcher to be its “head of preparedness.”
The hiring churn happening in Silicon Valley represents the “great unbundling” of the tech startup, as Dave Munichiello, an investor at GV, put it. In earlier eras, tech founders and their first employees often stayed onboard until either the lights went out or there was a major liquidity event. But in today’s market, where generative AI startups are growing rapidly, equipped with plenty of capital, and prized especially for the strength of their research talent, “you invest in a startup knowing it could be broken up,” Munichiello told me.
Early founders and researchers at the buzziest AI startups are bouncing around to different companies for a range of reasons. A big incentive for many, of course, is money. Last year Meta was reportedly offering top AI researchers compensation packages in the tens or hundreds of millions of dollars, offering them not just access to cutting-edge computing resources but also … generational wealth.
But it’s not all about getting rich. Broader cultural shifts that rocked the tech industry in recent years have made some workers worried about committing to one company or institution for too long, says Sayash Kapoor, a computer science researcher at Princeton University and a senior fellow at Mozilla. Employers used to safely assume that workers would stay at least until the four-year mark when their stock options were typically scheduled to vest. In the high-minded era of the 2000s and 2010s, plenty of early cofounders and employees also sincerely believed in the stated missions of their companies and wanted to be there to help achieve them.
Now, Kapoor says, “people understand the limitations of the institutions they’re working in, and founders are more pragmatic.” The founders of Windsurf, for example, may have calculated their impact could be larger at a place like Google that has lots of resources, Kapoor says. He adds that a similar shift is happening within academia. Over the past five years, Kapoor says, he’s seen more PhD researchers leave their computer-science doctoral programs to take jobs in industry. There are higher opportunity costs associated with staying in one place at a time when AI innovation is rapidly accelerating, he says.
Investors, wary of becoming collateral damage in the AI talent wars, are taking steps to protect themselves. Max Gazor, the founder of Striker Venture Partners, says his team is vetting founding teams “for chemistry and cohesion more than ever.” Gazor says it’s also increasingly common for deals to include “protective provisions that require board consent for material IP licensing or similar scenarios.”
Gazor notes that some of the biggest acqui-hire deals that have happened recently involved startups founded long before the current generative AI boom. Scale AI, for example, was founded in 2016, a time when the kind of deal Wang negotiated with Meta would have been unfathomable to many. Now, however, these potential outcomes might be considered in early term sheets and “constructively managed,” Gazor explains.
I asked my colleague Steven Levy, who has been reporting on Silicon Valley for decades, what he thought of this culture shift underway. He pointed out that working for an AI startup over the past few years has offered a lot of founders and top researchers an accelerated experience.
“Working for an AI startup for one year is equivalent to working for a startup for five years in a different era of tech,” Levy said. Teams can now launch brand-new products used by millions of people in a relatively short span of time, which leaves workers feeling like they’ve honed their skills enough to move on to a bigger challenge.
This generation of tech workers also has a wider range of opportunities to choose from than their predecessors did. Decades before Mira Murati’s Thinking Machines Lab was created, there was another startup called Thinking Machines Corporation working on parallel computing and artificial intelligence. One of its earliest employees, Lew Tucker, remembers there being around 50 people there when he joined in 1986, and more than 500 by the time the company went belly up and got acquired by Sun Microsystems in 1996. “Very few people left,” Tucker says. There were no job boards back then, either, he explains. People just “talked their way in.”
Even after tech went mainstream in the 2000’s, plenty of founders and early employees remained loyal to their firms. There were bragging rights that came with rejecting acquisition offers from big, bloated tech companies in favor of remaining committed to the startup cause. The founders and first-ins at companies like Google, Facebook, Airbnb, Stripe, Pinterest, Slack, Notion, and many others stuck around for years and reaped the rewards of their loyalty.
But the tech industry's halo has dimmed a lot since then. Founders, and their most loyal lieutenants, are trading idealism for pragmatism. AI is moving so fast, and the people developing it are trying to move along with it. There is little time to linger or build reputations slowly before the next opportunity arrives. For now, this generation of AI talent can name its price. The question is: at what cost?
Additional reporting by Paresh Dave.
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